VictoriaMetrics/lib/promscrape/scrapework.go

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package promscrape
import (
"flag"
"fmt"
"math"
"math/bits"
"strings"
"sync"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/leveledbytebufferpool"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/promauth"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/promrelabel"
parser "github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/prometheus"
"github.com/VictoriaMetrics/metrics"
xxhash "github.com/cespare/xxhash/v2"
)
var (
suppressScrapeErrors = flag.Bool("promscrape.suppressScrapeErrors", false, "Whether to suppress scrape errors logging. "+
"The last error for each target is always available at '/targets' page even if scrape errors logging is suppressed")
)
// ScrapeWork represents a unit of work for scraping Prometheus metrics.
type ScrapeWork struct {
// Unique ID for the ScrapeWork.
ID uint64
// Full URL (including query args) for the scrape.
ScrapeURL string
// Interval for scraping the ScrapeURL.
ScrapeInterval time.Duration
// Timeout for scraping the ScrapeURL.
ScrapeTimeout time.Duration
// How to deal with conflicting labels.
// See https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config
HonorLabels bool
// How to deal with scraped timestamps.
// See https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config
HonorTimestamps bool
// OriginalLabels contains original labels before relabeling.
//
// These labels are needed for relabeling troubleshooting at /targets page.
OriginalLabels []prompbmarshal.Label
// Labels to add to the scraped metrics.
//
// The list contains at least the following labels according to https://prometheus.io/docs/prometheus/latest/configuration/configuration/#relabel_config
//
// * job
// * __address__
// * __scheme__
// * __metrics_path__
// * __param_<name>
// * __meta_*
// * user-defined labels set via `relabel_configs` section in `scrape_config`
//
// See also https://prometheus.io/docs/concepts/jobs_instances/
Labels []prompbmarshal.Label
// Auth config
AuthConfig *promauth.Config
// Optional `metric_relabel_configs`.
MetricRelabelConfigs []promrelabel.ParsedRelabelConfig
// The maximum number of metrics to scrape after relabeling.
SampleLimit int
// Whether to disable response compression when querying ScrapeURL.
DisableCompression bool
// Whether to disable HTTP keep-alive when querying ScrapeURL.
DisableKeepAlive bool
// Whether to parse target responses in a streaming manner.
StreamParse bool
// The original 'job_name'
jobNameOriginal string
}
// key returns unique identifier for the given sw.
//
// it can be used for comparing for equality for two ScrapeWork objects.
func (sw *ScrapeWork) key() string {
// Do not take into account OriginalLabels.
key := fmt.Sprintf("ScrapeURL=%s, ScrapeInterval=%s, ScrapeTimeout=%s, HonorLabels=%v, HonorTimestamps=%v, Labels=%s, "+
"AuthConfig=%s, MetricRelabelConfigs=%s, SampleLimit=%d, DisableCompression=%v, DisableKeepAlive=%v, StreamParse=%v",
sw.ScrapeURL, sw.ScrapeInterval, sw.ScrapeTimeout, sw.HonorLabels, sw.HonorTimestamps, sw.LabelsString(),
sw.AuthConfig.String(), sw.metricRelabelConfigsString(), sw.SampleLimit, sw.DisableCompression, sw.DisableKeepAlive, sw.StreamParse)
return key
}
func (sw *ScrapeWork) metricRelabelConfigsString() string {
var sb strings.Builder
for _, prc := range sw.MetricRelabelConfigs {
fmt.Fprintf(&sb, "%s", prc.String())
}
return sb.String()
}
// Job returns job for the ScrapeWork
func (sw *ScrapeWork) Job() string {
return promrelabel.GetLabelValueByName(sw.Labels, "job")
}
// LabelsString returns labels in Prometheus format for the given sw.
func (sw *ScrapeWork) LabelsString() string {
labelsFinalized := promrelabel.FinalizeLabels(nil, sw.Labels)
return promLabelsString(labelsFinalized)
}
func promLabelsString(labels []prompbmarshal.Label) string {
a := make([]string, 0, len(labels))
for _, label := range labels {
a = append(a, fmt.Sprintf("%s=%q", label.Name, label.Value))
}
return "{" + strings.Join(a, ", ") + "}"
}
type scrapeWork struct {
// Config for the scrape.
Config ScrapeWork
// ReadData is called for reading the data.
ReadData func(dst []byte) ([]byte, error)
// GetStreamReader is called if Config.StreamParse is set.
GetStreamReader func() (*streamReader, error)
// PushData is called for pushing collected data.
PushData func(wr *prompbmarshal.WriteRequest)
// ScrapeGroup is name of ScrapeGroup that
// scrapeWork belongs to
ScrapeGroup string
tmpRow parser.Row
// the seriesMap, seriesAdded and labelsHashBuf are used for fast calculation of `scrape_series_added` metric.
seriesMap map[uint64]struct{}
seriesAdded int
labelsHashBuf []byte
// prevBodyLen contains the previous response body length for the given scrape work.
// It is used as a hint in order to reduce memory usage for body buffers.
prevBodyLen int
// prevRowsLen contains the number rows scraped during the previous scrape.
// It is used as a hint in order to reduce memory usage when parsing scrape responses.
prevRowsLen int
}
func (sw *scrapeWork) run(stopCh <-chan struct{}) {
// Calculate start time for the first scrape from ScrapeURL and labels.
// This should spread load when scraping many targets with different
// scrape urls and labels.
// This also makes consistent scrape times across restarts
// for a target with the same ScrapeURL and labels.
scrapeInterval := sw.Config.ScrapeInterval
key := fmt.Sprintf("ScrapeURL=%s, Labels=%s", sw.Config.ScrapeURL, sw.Config.LabelsString())
h := uint32(xxhash.Sum64([]byte(key)))
randSleep := uint64(float64(scrapeInterval) * (float64(h) / (1 << 32)))
sleepOffset := uint64(time.Now().UnixNano()) % uint64(scrapeInterval)
if randSleep < sleepOffset {
randSleep += uint64(scrapeInterval)
}
randSleep -= sleepOffset
timer := time.NewTimer(time.Duration(randSleep))
var timestamp int64
var ticker *time.Ticker
select {
case <-stopCh:
timer.Stop()
return
case <-timer.C:
ticker = time.NewTicker(scrapeInterval)
timestamp = time.Now().UnixNano() / 1e6
sw.scrapeAndLogError(timestamp, timestamp)
}
defer ticker.Stop()
for {
timestamp += scrapeInterval.Milliseconds()
select {
case <-stopCh:
return
case tt := <-ticker.C:
t := tt.UnixNano() / 1e6
if d := math.Abs(float64(t - timestamp)); d > 0 && d/float64(scrapeInterval.Milliseconds()) > 0.1 {
// Too big jitter. Adjust timestamp
timestamp = t
}
sw.scrapeAndLogError(timestamp, t)
}
}
}
func (sw *scrapeWork) logError(s string) {
if !*suppressScrapeErrors {
logger.ErrorfSkipframes(1, "error when scraping %q from job %q with labels %s: %s", sw.Config.ScrapeURL, sw.Config.Job(), sw.Config.LabelsString(), s)
}
}
func (sw *scrapeWork) scrapeAndLogError(scrapeTimestamp, realTimestamp int64) {
if err := sw.scrapeInternal(scrapeTimestamp, realTimestamp); err != nil && !*suppressScrapeErrors {
logger.Errorf("error when scraping %q from job %q with labels %s: %s", sw.Config.ScrapeURL, sw.Config.Job(), sw.Config.LabelsString(), err)
}
}
var (
scrapeDuration = metrics.NewHistogram("vm_promscrape_scrape_duration_seconds")
scrapeResponseSize = metrics.NewHistogram("vm_promscrape_scrape_response_size_bytes")
scrapedSamples = metrics.NewHistogram("vm_promscrape_scraped_samples")
scrapesSkippedBySampleLimit = metrics.NewCounter("vm_promscrape_scrapes_skipped_by_sample_limit_total")
scrapesFailed = metrics.NewCounter("vm_promscrape_scrapes_failed_total")
pushDataDuration = metrics.NewHistogram("vm_promscrape_push_data_duration_seconds")
)
func (sw *scrapeWork) scrapeInternal(scrapeTimestamp, realTimestamp int64) error {
if *streamParse || sw.Config.StreamParse {
// Read data from scrape targets in streaming manner.
// This case is optimized for targets exposing millions and more of metrics per target.
return sw.scrapeStream(scrapeTimestamp, realTimestamp)
}
// Common case: read all the data from scrape target to memory (body) and then process it.
// This case should work more optimally for than stream parse code above for common case when scrape target exposes
// up to a few thouthand metrics.
body := leveledbytebufferpool.Get(sw.prevBodyLen)
var err error
body.B, err = sw.ReadData(body.B[:0])
endTimestamp := time.Now().UnixNano() / 1e6
duration := float64(endTimestamp-realTimestamp) / 1e3
scrapeDuration.Update(duration)
scrapeResponseSize.Update(float64(len(body.B)))
up := 1
wc := writeRequestCtxPool.Get(sw.prevRowsLen)
if err != nil {
up = 0
scrapesFailed.Inc()
} else {
bodyString := bytesutil.ToUnsafeString(body.B)
wc.rows.UnmarshalWithErrLogger(bodyString, sw.logError)
}
srcRows := wc.rows.Rows
samplesScraped := len(srcRows)
scrapedSamples.Update(float64(samplesScraped))
if sw.Config.SampleLimit > 0 && samplesScraped > sw.Config.SampleLimit {
srcRows = srcRows[:0]
up = 0
scrapesSkippedBySampleLimit.Inc()
}
samplesPostRelabeling := 0
for i := range srcRows {
sw.addRowToTimeseries(wc, &srcRows[i], scrapeTimestamp, true)
if len(wc.labels) > 40000 {
// Limit the maximum size of wc.writeRequest.
// This should reduce memory usage when scraping targets with millions of metrics and/or labels.
// For example, when scraping /federate handler from Prometheus - see https://prometheus.io/docs/prometheus/latest/federation/
samplesPostRelabeling += len(wc.writeRequest.Timeseries)
sw.updateSeriesAdded(wc)
startTime := time.Now()
sw.PushData(&wc.writeRequest)
pushDataDuration.UpdateDuration(startTime)
wc.resetNoRows()
}
}
samplesPostRelabeling += len(wc.writeRequest.Timeseries)
sw.updateSeriesAdded(wc)
seriesAdded := sw.finalizeSeriesAdded(samplesPostRelabeling)
sw.addAutoTimeseries(wc, "up", float64(up), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_duration_seconds", duration, scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_samples_scraped", float64(samplesScraped), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_samples_post_metric_relabeling", float64(samplesPostRelabeling), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_series_added", float64(seriesAdded), scrapeTimestamp)
startTime := time.Now()
sw.PushData(&wc.writeRequest)
pushDataDuration.UpdateDuration(startTime)
sw.prevRowsLen = samplesScraped
wc.reset()
writeRequestCtxPool.Put(wc)
// body must be released only after wc is released, since wc refers to body.
sw.prevBodyLen = len(body.B)
leveledbytebufferpool.Put(body)
tsmGlobal.Update(&sw.Config, sw.ScrapeGroup, up == 1, realTimestamp, int64(duration*1000), err)
return err
}
func (sw *scrapeWork) scrapeStream(scrapeTimestamp, realTimestamp int64) error {
sr, err := sw.GetStreamReader()
if err != nil {
return fmt.Errorf("cannot read data: %s", err)
}
samplesScraped := 0
samplesPostRelabeling := 0
wc := writeRequestCtxPool.Get(sw.prevRowsLen)
var mu sync.Mutex
err = parser.ParseStream(sr, scrapeTimestamp, false, func(rows []parser.Row) error {
mu.Lock()
defer mu.Unlock()
samplesScraped += len(rows)
for i := range rows {
sw.addRowToTimeseries(wc, &rows[i], scrapeTimestamp, true)
if len(wc.labels) > 40000 {
// Limit the maximum size of wc.writeRequest.
// This should reduce memory usage when scraping targets with millions of metrics and/or labels.
// For example, when scraping /federate handler from Prometheus - see https://prometheus.io/docs/prometheus/latest/federation/
samplesPostRelabeling += len(wc.writeRequest.Timeseries)
sw.updateSeriesAdded(wc)
startTime := time.Now()
sw.PushData(&wc.writeRequest)
pushDataDuration.UpdateDuration(startTime)
wc.resetNoRows()
}
}
return nil
})
scrapedSamples.Update(float64(samplesScraped))
endTimestamp := time.Now().UnixNano() / 1e6
duration := float64(endTimestamp-realTimestamp) / 1e3
scrapeDuration.Update(duration)
scrapeResponseSize.Update(float64(sr.bytesRead))
sr.MustClose()
up := 1
if err != nil {
if samplesScraped == 0 {
up = 0
}
scrapesFailed.Inc()
}
samplesPostRelabeling += len(wc.writeRequest.Timeseries)
sw.updateSeriesAdded(wc)
seriesAdded := sw.finalizeSeriesAdded(samplesPostRelabeling)
sw.addAutoTimeseries(wc, "up", float64(up), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_duration_seconds", duration, scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_samples_scraped", float64(samplesScraped), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_samples_post_metric_relabeling", float64(samplesPostRelabeling), scrapeTimestamp)
sw.addAutoTimeseries(wc, "scrape_series_added", float64(seriesAdded), scrapeTimestamp)
startTime := time.Now()
sw.PushData(&wc.writeRequest)
pushDataDuration.UpdateDuration(startTime)
sw.prevRowsLen = len(wc.rows.Rows)
wc.reset()
writeRequestCtxPool.Put(wc)
tsmGlobal.Update(&sw.Config, sw.ScrapeGroup, up == 1, realTimestamp, int64(duration*1000), err)
return nil
}
// leveledWriteRequestCtxPool allows reducing memory usage when writeRequesCtx
// structs contain mixed number of labels.
//
// Its logic has been copied from leveledbytebufferpool.
type leveledWriteRequestCtxPool struct {
pools [30]sync.Pool
}
func (lwp *leveledWriteRequestCtxPool) Get(rowsCapacity int) *writeRequestCtx {
id, capacityNeeded := lwp.getPoolIDAndCapacity(rowsCapacity)
for i := 0; i < 2; i++ {
if id < 0 || id >= len(lwp.pools) {
break
}
if v := lwp.pools[id].Get(); v != nil {
return v.(*writeRequestCtx)
}
id++
}
return &writeRequestCtx{
labels: make([]prompbmarshal.Label, 0, capacityNeeded),
}
}
func (lwp *leveledWriteRequestCtxPool) Put(wc *writeRequestCtx) {
capacity := cap(wc.rows.Rows)
id, _ := lwp.getPoolIDAndCapacity(capacity)
wc.reset()
lwp.pools[id].Put(wc)
}
func (lwp *leveledWriteRequestCtxPool) getPoolIDAndCapacity(size int) (int, int) {
size--
if size < 0 {
size = 0
}
size >>= 3
id := bits.Len(uint(size))
if id > len(lwp.pools) {
id = len(lwp.pools) - 1
}
return id, (1 << (id + 3))
}
type writeRequestCtx struct {
rows parser.Rows
writeRequest prompbmarshal.WriteRequest
labels []prompbmarshal.Label
samples []prompbmarshal.Sample
}
func (wc *writeRequestCtx) reset() {
wc.rows.Reset()
wc.resetNoRows()
}
func (wc *writeRequestCtx) resetNoRows() {
prompbmarshal.ResetWriteRequest(&wc.writeRequest)
wc.labels = wc.labels[:0]
wc.samples = wc.samples[:0]
}
var writeRequestCtxPool leveledWriteRequestCtxPool
func (sw *scrapeWork) updateSeriesAdded(wc *writeRequestCtx) {
if sw.seriesMap == nil {
sw.seriesMap = make(map[uint64]struct{}, len(wc.writeRequest.Timeseries))
}
m := sw.seriesMap
for _, ts := range wc.writeRequest.Timeseries {
h := sw.getLabelsHash(ts.Labels)
if _, ok := m[h]; !ok {
m[h] = struct{}{}
sw.seriesAdded++
}
}
}
func (sw *scrapeWork) finalizeSeriesAdded(lastScrapeSize int) int {
seriesAdded := sw.seriesAdded
sw.seriesAdded = 0
2020-09-11 21:14:04 +00:00
if len(sw.seriesMap) > 4*lastScrapeSize {
// Reset seriesMap, since it occupies more than 4x metrics collected during the last scrape.
sw.seriesMap = make(map[uint64]struct{}, lastScrapeSize)
}
return seriesAdded
}
func (sw *scrapeWork) getLabelsHash(labels []prompbmarshal.Label) uint64 {
// It is OK if there will be hash collisions for distinct sets of labels,
// since the accuracy for `scrape_series_added` metric may be lower than 100%.
b := sw.labelsHashBuf[:0]
for _, label := range labels {
b = append(b, label.Name...)
b = append(b, label.Value...)
}
sw.labelsHashBuf = b
return xxhash.Sum64(b)
}
// addAutoTimeseries adds automatically generated time series with the given name, value and timestamp.
//
// See https://prometheus.io/docs/concepts/jobs_instances/#automatically-generated-labels-and-time-series
func (sw *scrapeWork) addAutoTimeseries(wc *writeRequestCtx, name string, value float64, timestamp int64) {
sw.tmpRow.Metric = name
sw.tmpRow.Tags = nil
sw.tmpRow.Value = value
sw.tmpRow.Timestamp = timestamp
sw.addRowToTimeseries(wc, &sw.tmpRow, timestamp, false)
}
func (sw *scrapeWork) addRowToTimeseries(wc *writeRequestCtx, r *parser.Row, timestamp int64, needRelabel bool) {
labelsLen := len(wc.labels)
wc.labels = appendLabels(wc.labels, r.Metric, r.Tags, sw.Config.Labels, sw.Config.HonorLabels)
if needRelabel {
wc.labels = promrelabel.ApplyRelabelConfigs(wc.labels, labelsLen, sw.Config.MetricRelabelConfigs, true)
} else {
wc.labels = promrelabel.FinalizeLabels(wc.labels[:labelsLen], wc.labels[labelsLen:])
promrelabel.SortLabels(wc.labels[labelsLen:])
}
if len(wc.labels) == labelsLen {
// Skip row without labels.
return
}
sampleTimestamp := r.Timestamp
if !sw.Config.HonorTimestamps || sampleTimestamp == 0 {
sampleTimestamp = timestamp
}
wc.samples = append(wc.samples, prompbmarshal.Sample{
Value: r.Value,
Timestamp: sampleTimestamp,
})
wr := &wc.writeRequest
wr.Timeseries = append(wr.Timeseries, prompbmarshal.TimeSeries{
Labels: wc.labels[labelsLen:],
Samples: wc.samples[len(wc.samples)-1:],
})
}
func appendLabels(dst []prompbmarshal.Label, metric string, src []parser.Tag, extraLabels []prompbmarshal.Label, honorLabels bool) []prompbmarshal.Label {
dstLen := len(dst)
dst = append(dst, prompbmarshal.Label{
Name: "__name__",
Value: metric,
})
for i := range src {
tag := &src[i]
dst = append(dst, prompbmarshal.Label{
Name: tag.Key,
Value: tag.Value,
})
}
dst = append(dst, extraLabels...)
labels := dst[dstLen:]
if len(labels) <= 1 {
// Fast path - only a single label.
return dst
}
// de-duplicate labels
dstLabels := labels[:0]
for i := range labels {
label := &labels[i]
prevLabel := promrelabel.GetLabelByName(dstLabels, label.Name)
if prevLabel == nil {
dstLabels = append(dstLabels, *label)
continue
}
if honorLabels {
// Skip the extra label with the same name.
continue
}
// Rename the prevLabel to "exported_" + label.Name.
// See https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config
exportedName := "exported_" + label.Name
if promrelabel.GetLabelByName(dstLabels, exportedName) != nil {
// Override duplicate with the current label.
*prevLabel = *label
continue
}
prevLabel.Name = exportedName
dstLabels = append(dstLabels, *label)
}
return dst[:dstLen+len(dstLabels)]
}